Cart (Loading....) | Create Account
Close category search window
 

Long-range dependence in heart rate variability data: ARFIMA modelling vs detrended fluctuation analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Leite, A. ; Dept. de Matemetica Aplic., Univ. do Porto, Porto ; Rocha, A.P. ; Silva, M.E. ; Gouveia, S.
more authors

Heart rate variability (HRV) data display non-stationary characteristics and exhibit long-range correlation (memory). Detrended fluctuation analysis (DFA) has become a widely-used technique for long memory estimation in non-stationary HRV data. Recently, we have proposed an alternative approach based on fractional integrated autoregressive moving average (ARFIMA) models. ARFIMA models, combined with selective adaptive segmentation may be used to capture and remove long-range correlation, leading to an improved description and interpretation of the components in 24 hour HRV recordings. In this work estimation of long memory by DFA and selective adaptive ARFIMA modelling is carried out in 24 hour HRV recordings of 17 healthy subjects of two age groups. The two methods give similar information on long-range global characteristics. However, ARFIMA modelling is advantageous, allowing the description of long-range correlation in reduced length segments.

Published in:

Computers in Cardiology, 2007

Date of Conference:

Sept. 30 2007-Oct. 3 2007

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.